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The variational quantum eigensolver is a hybrid algorithm composed of quantum state driving and classical parameter optimization, for finding the ground state of a given Hamiltonian.
J. C. Spall, Multivariate stochastic approximation using a simultaneous perturbation gradient approximation, IEEE Trans. Autom. Contr. 37, 332-341 (1992)
1992
Earlier work this paper cites.
1994
Earlier work this paper cites.
S. Amari, Natural gradient works efficiently in learning, Neural Computation, 10, 251/276 (1998)
1998
Earlier work this paper cites.
S. Sorella. Generalized Lanczos algorithm for variational quantum Monte Carlo, Phys. Rev. B 64, 024512 (2001)
2001
Earlier work this paper cites.
M. Casula C. Attaccalite, and S. Sorella. Correlated geminal wave function for molecules: An efficient resonating valence bond approach. Journal. Chem. Phys. 121, 7110 (2004)
2004
Earlier work this paper cites.
A. Peruzzo, J. McClean, P. Shadbolt, M. Yung, X. Zhou, P. J. Love, A. Aspuru-Guzik, and J. L. O’Brien, A variational eigenvalue solver on a photonic quantum processor, Nat. Commun. 5, 4213 (2014)
2014
Earlier work this paper cites.
J. R. McClean, J. Romero, R. Babbush, and A. Aspuru-Guzik, The theory of variational hybrid quantum-classical algorithms, New J. Phys. 18, 023023 (2016)
2016
Cited alongside, same era.
A. Kandala, A. Mezzacapo, K. Temme, M. Takita, M. Brink, J. M. Chow, and J. M. Gambetta, Hardware-efficient variational quantum eigensolver for small molecules and quantum magnets, Nature 549, 242 (2017)
2017
Cited alongside, same era.
2017
Cited alongside, same era.
G. Carleo and M. Troyer, Solving the quantum many-body problem with artificial neural networks, Science 355, 602 (2017)
2017
Cited alongside, same era.
I. Glasser, N. Pancotti, M. August, I. D. Rodriguez, and J. I. Cirac, Neural-network quantum states, string-bond states, and Chiral topological states, Phys. Rev. X 8, 011006 (2018)
2018
Later among the works it cites.
2018
Later among the works it cites.
H. R. Grimsley, S. E. Economou, E. Barnes, and N. J. Mayhall, An adaptive variational algorithm for exact molecular simulations on a quantum computer, Nat. Commun. 10, 3007 (2019)
2019
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2019
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J. Stokes, J. Izaac, N. Killoran, and G. Carleo, Quantum natural gradient, arXiv:1909.02108 (2019)
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2018
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2019
Closest in time.